1. Technical Field
The invention relates to signal processing methods, particularly to calculating values from correlated sample values (such as a neighborhood) in signal enhancement applications.
2. Background
It is a common goal in signal processing to attempt to enhance the quality of given content. Some methods exist to achieve better results than simple linear convolution filters and interpolation methods such as bi-linear filters, tri-linear filters, bi-cubic filters, tri-cubic filters, Laplace filters and Lanczos filters. Another method includes “classifying” the neighborhood using different methods (gradient, pattern matching, clustering, edge detection, optical flow) and select specific convolution filters, or combine convolution filters based on that classification, such as the method described in U.S. Pat. No. 6,133,957. Still another method attempts to calculate appropriate values based on coarser-scale characteristics of the dataset. Some methods then take a least square approach to determine the convolution coefficients for each “class” of neighborhood. In effect, all these methods are defining non-linear filter functions of the neighborhood with some heuristic approach. Most known methods suffer from computational complexity while others suffer from artifacts and mediocre image quality.